Search results
Found 16089 matches for
Led by Professor Andrea Cipriani the 3-day interactive course will give participants knowledge and practical skills on how to understand, critically appraise and publish a network meta-analysis.
What challenges do siblings of children with chronic disorders express to their parents? A thematic analysis of 73 sibling-parent dialogues.
PURPOSE: The study explored challenges experienced by siblings of children with chronic disorders, as expressed by siblings in parent-child dialogues. DESIGN AND METHODS: Seventy-three parent-child dialogues (M duration = 28.6 min) were analyzed using qualitative thematic analysis. The dialogues took place within the SIBS group intervention for siblings and parents of children with chronic disorders. The siblings (aged 8 to 14 years) had brothers and sisters with autism spectrum disorders, ADHD, rare disorders, cerebral palsy, or severe mental health disorders. The data are from session 5 in the SIBS intervention, in which the siblings are to express their wishes about family-related challenges (e.g., desired changes) to their parents. The parents are encouraged to listen, explore, and validate the child's perspective before discussing solutions. RESULTS: Most of the family-oriented challenges the siblings expressed were related to the diagnosis of the brother or sister with a disorder. Four main themes were identified: (1) Family life (e.g., limitations in family activities); (2) The diagnosis (e.g., concerns about the future); (3) Violence; and (4) Important relationships. CONCLUSION: The siblings experienced challenges and difficult emotions in interactional processes in which the diagnosis affected family life and relationships. The study adds a new dimension to the field by identifying siblings' expressed challenges based on parent-child dialogues. PRACTICE IMPLICATIONS: Identified themes can guide how parents should meet and address siblings' needs, how health care providers inform and support parents in doing so, and emphasize the relevance of interventions targeting family-level risk and resilience factors.
Does the duration of illness before treatment affect the time taken to recover on treatment in severely depressed women?
This study examines the link between duration of depression before treatment is introduced and the duration of depressive illness after treatment in a population of 59 female psychiatric inpatients. Most women were suffering with severe depression and the majority had had previous depressive illnesses. Calculation of the rank order correlation coefficient demonstrated no significant correlation between the duration of depression before initiation of treatment and the duration after treatment was introduced. This finding is discussed in relation to other relevant studies.
18FDG PET-CT in sporadic Creutzfeldt-Jakob disease, correlated with MRI and histology.
We present a case of sporadic Creutzfeldt-Jakob disease with profoundly abnormal 18fluoro-deoxy-glucose positron emission tomography with computed tomography (FDG PET-CT) at an early stage, and correlate this with the clear findings at magnetic resonance imaging and also postmortem histology. Prion diseases are rare but important causes of cognitive impairment. The role of FDG PET-CT is discussed, along with other investigations such as electroencephalography and cerebro-spinal fluid analyses.
Acceptance and commitment therapy for older people with treatment-resistant generalised anxiety disorder: the FACTOID feasibility study.
BACKGROUND: Generalised anxiety disorder, characterised by excessive anxiety and worry, is the most common anxiety disorder among older people. It is a condition that may persist for decades and is associated with numerous negative outcomes. Front-line treatments include pharmacological and psychological therapy, but many older people do not find these treatments effective. Guidance on managing treatment-resistant generalised anxiety disorder in older people is lacking. OBJECTIVES: To assess whether or not a study to examine the clinical effectiveness and cost-effectiveness of acceptance and commitment therapy for older people with treatment-resistant generalised anxiety disorder is feasible, we developed an intervention based on acceptance and commitment therapy for this population, assessed its acceptability and feasibility in an uncontrolled feasibility study and clarified key study design parameters. DESIGN: Phase 1 involved qualitative interviews to develop and optimise an intervention as well as a survey of service users and clinicians to clarify usual care. Phase 2 involved an uncontrolled feasibility study and qualitative interviews to refine the intervention. SETTING: Participants were recruited from general practices, Improving Access to Psychological Therapies services, Community Mental Health Teams and the community. PARTICIPANTS: Participants were people aged ≥ 65 years with treatment-resistant generalised anxiety disorder. INTERVENTION: Participants received up to 16 one-to-one sessions of acceptance and commitment therapy, adapted for older people with treatment-resistant generalised anxiety disorder, in addition to usual care. Sessions were delivered by therapists based in primary and secondary care services, either in the clinic or at participants' homes. Sessions were weekly for the first 14 sessions and fortnightly thereafter. MAIN OUTCOME MEASURES: The co-primary outcome measures for phase 2 were acceptability (session attendance and satisfaction with therapy) and feasibility (recruitment and retention). Secondary outcome measures included additional measures of acceptability and feasibility and self-reported measures of anxiety, worry, depression and psychological flexibility. Self-reported outcomes were assessed at 0 weeks (baseline) and 20 weeks (follow-up). Health economic outcomes included intervention and resource use costs and health-related quality of life. RESULTS: Fifteen older people with treatment-resistant generalised anxiety disorder participated in phase 1 and 37 participated in phase 2. A high level of feasibility was demonstrated by a recruitment rate of 93% and a retention rate of 81%. A high level of acceptability was found with respect to session attendance (70% of participants attended ≥ 10 sessions) and satisfaction with therapy was adequate (60% of participants scored ≥ 21 out of 30 points on the Satisfaction with Therapy subscale of the Satisfaction with Therapy and Therapist Scale-Revised, although 80% of participants had not finished receiving therapy at the time of rating). Secondary outcome measures and qualitative data further supported the feasibility and acceptability of the intervention. Health economic data supported the feasibility of examining cost-effectiveness in a future randomised controlled trial. Although the study was not powered to examine clinical effectiveness, there was indicative evidence of improvements in scores for anxiety, depression and psychological flexibility. LIMITATIONS: Non-specific therapeutic factors were not controlled for, and recruitment in phase 2 was limited to London. CONCLUSIONS: There was evidence of high levels of feasibility and acceptability and indicative evidence of improvements in symptoms of anxiety, depression and psychological flexibility. The results of this study suggest that a larger-scale randomised controlled trial would be feasible to conduct and is warranted. TRIAL REGISTRATION: Current Controlled Trials ISRCTN12268776. FUNDING: This project was funded by the National Institute for Health Research (NIHR) Health Technology Assessment programme and will be published in full in Health Technology Assessment; Vol. 25, No. 54. See the NIHR Journals Library website for further project information.
Adapted problem adaptation therapy for depression in mild to moderate Alzheimer's disease dementia: A randomized controlled trial.
INTRODUCTION: Trials of effectiveness of treatment options for depression in dementia are an important priority. METHODS: Randomized controlled trial to assess adapted Problem Adaptation Therapy (PATH) for depression in mild/moderate dementia caused by Alzheimer's disease. RESULTS: Three hundred thirty-six participants with mild or moderate dementia, >7 on Cornell Scale for Depression in Dementia (CSDD), randomized to adapted PATH or treatment as usual. Mean age 77.0 years, 39.0% males, mean Mini-Mental State Examination 21.6, mean CSDD 12.9. For primary outcome (CSDD at 6 months), no statistically significant benefit with adapted PATH on the CSDD (6 months: -0.58; 95% CI -1.71 to 0.54). The CSDD at 3 months showed a small benefit with adapted PATH (-1.38; 95% CI -2.54 to -0.21) as did the EQ-5D (-4.97; 95% CI -9.46 to -0.48). DISCUSSION: An eight-session course of adapted PATH plus two booster sessions administered within NHS dementia services was not effective treatment for depression in people with mild and moderate dementia. Future studies should examine the effect of more intensive and longer-term therapy.
Trace amine-associated receptor 1 (TAAR1) agonists for psychosis: protocol for a living systematic review and meta-analysis of human and non-human studies.
BackgroundThere is an urgent need to develop more effective and safer antipsychotics beyond dopamine 2 receptor antagonists. An emerging and promising approach is TAAR1 agonism. Therefore, we will conduct a living systematic review and meta-analysis to synthesize and triangulate the evidence from preclinical animal experiments and clinical studies on the efficacy, safety, and underlying mechanism of action of TAAR1 agonism for psychosis.MethodsIndependent searches will be conducted in multiple electronic databases to identify clinical and animal experimental studies comparing TAAR1 agonists with licensed antipsychotics or other control conditions in individuals with psychosis or animal models for psychosis, respectively. The primary outcomes will be overall psychotic symptoms and their behavioural proxies in animals. Secondary outcomes will include side effects and neurobiological measures. Two independent reviewers will conduct study selection, data extraction using predefined forms, and risk of bias assessment using suitable tools based on the study design. Ontologies will be developed to facilitate study identification and data extraction. Data from clinical and animal studies will be synthesized separately using random-effects meta-analysis if appropriate, or synthesis without meta-analysis. Study characteristics will be investigated as potential sources of heterogeneity. Confidence in the evidence for each outcome and source of evidence will be evaluated, considering the summary of the association, potential concerns regarding internal and external validity, and reporting biases. When multiple sources of evidence are available for an outcome, an overall conclusion will be drawn in a triangulation meeting involving a multidisciplinary team of experts. We plan trimonthly updates of the review, and any modifications in the protocol will be documented. The review will be co-produced by multiple stakeholders aiming to produce impactful and relevant results and bridge the gap between preclinical and clinical research on psychosis.Protocol registrationPROSPERO-ID: CRD42023451628.
When a test is more than just a test: Findings from patient interviews and survey in the trial of a technology to measure antidepressant medication response (the PReDicT Trial).
BACKGROUND: A RCT of a novel intervention to detect antidepressant medication response (the PReDicT Test) took place in five European countries, accompanied by a nested study of its acceptability and implementation presented here. The RCT results indicated no effect of the intervention on depression at 8 weeks (primary outcome), although effects on anxiety at 8 weeks and functioning at 24 weeks were found. METHODS: The nested study used mixed methods. The aim was to explore patient experiences of the Test including acceptability and implementation, to inform its use within care. A bespoke survey was completed by trial participants in five countries (n = 778) at week 8. Semi-structured interviews were carried out in two countries soon after week 8 (UK n = 22, Germany n = 20). Quantitative data was analysed descriptively; for qualitative data, thematic analysis was carried out using a framework approach. Results of the two datasets were interrogated together. OUTCOMES: Survey results showed the intervention was well received, with a majority of participants indicating they would use it again, and it gave them helpful extra information; a small minority indicated the Test made them feel worse. Qualitative data showed the Test had unexpected properties, including: instigating a process of reflection, giving participants feedback on progress and new understanding about their illness, and making participants feel supported and more engaged in treatment. INTERPRETATION: The qualitative and quantitative results are generally consistent. The Test's unexpected properties may explain why the RCT showed little effect, as properties were experienced across both trial arms. Beyond the RCT, the qualitative data sheds light on measurement reactivity, i.e., how measurements of depression can impact patients.
Distress and neuroticism as mediators of the effect of childhood and adulthood adversity on cognitive performance in the UK Biobank study.
Childhood adversity and adulthood adversity affect cognition later in life. However, the mechanism through which adversity exerts these effects on cognition remains under-researched. We aimed to investigate if the effect of adversity on cognition was mediated by distress or neuroticism. The UK Biobank is a large, population-based, cohort study designed to investigate risk factors of cognitive health. Here, data were analysed using a cross-sectional design. Structural equation models were fitted to the data with childhood adversity or adulthood adversity as independent variables, distress and neuroticism as mediators and executive function and processing speed as latent dependent variables that were derived from the cognitive scores in the UK Biobank. Complete data were available for 64,051 participants in the childhood adversity model and 63,360 participants in the adulthood adversity model. Childhood adversity did not show a direct effect on processing speed. The effect of childhood adversity on executive function was partially mediated by distress and neuroticism. The effects of adulthood adversity on executive function and processing speed were both partially mediated by distress and neuroticism. In conclusion, distress and neuroticism mediated the deleterious effect of childhood and adulthood adversity on cognition and may provide a mechanism underlying the deleterious consequences of adversity.
Artificial intelligence for dementia genetics and omics.
Genetics and omics studies of Alzheimer's disease and other dementia subtypes enhance our understanding of underlying mechanisms and pathways that can be targeted. We identified key remaining challenges: First, can we enhance genetic studies to address missing heritability? Can we identify reproducible omics signatures that differentiate between dementia subtypes? Can high-dimensional omics data identify improved biomarkers? How can genetics inform our understanding of causal status of dementia risk factors? And which biological processes are altered by dementia-related genetic variation? Artificial intelligence (AI) and machine learning approaches give us powerful new tools in helping us to tackle these challenges, and we review possible solutions and examples of best practice. However, their limitations also need to be considered, as well as the need for coordinated multidisciplinary research and diverse deeply phenotyped cohorts. Ultimately AI approaches improve our ability to interrogate genetics and omics data for precision dementia medicine. HIGHLIGHTS: We have identified five key challenges in dementia genetics and omics studies. AI can enable detection of undiscovered patterns in dementia genetics and omics data. Enhanced and more diverse genetics and omics datasets are still needed. Multidisciplinary collaborative efforts using AI can boost dementia research.
Trace amine-associated receptor 1 (TAAR1) agonism for psychosis: a living systematic review and meta-analysis of human and non-human data
Background Trace amine-associated receptor 1 (TAAR1) agonism shows promise for treating psychosis, prompting us to synthesise data from human and non-human studies. Methods We co-produced a living systematic review of controlled studies examining TAAR1 agonists in individuals (with or without psychosis/schizophrenia) and relevant animal models. Two independent reviewers identified studies in multiple electronic databases (until 17.11.2023), extracted data, and assessed risk of bias. Primary outcomes were standardised mean differences (SMD) for overall symptoms in human studies and hyperlocomotion in animal models. We also examined adverse events and neurotransmitter signalling. We synthesised data with random-effects meta-analyses. Results Nine randomised trials provided data for two TAAR1 agonists (ulotaront and ralmitaront), and 15 animal studies for 10 TAAR1 agonists. Ulotaront and ralmitaront demonstrated few differences compared to placebo in improving overall symptoms in adults with acute schizophrenia (N=4 studies, n=1291 participants; SMD=0.15, 95%CI: -0.05, 0.34), and ralmitaront was less efficacious than risperidone (N=1, n=156, SMD=-0.53, 95%CI: -0.86, -0.20). Large placebo response was observed in ulotaront phase-III trials. Limited evidence suggested a relatively benign side-effect profile for TAAR1 agonists, although nausea and sedation were common after a single dose of ulotaront. In animal studies, TAAR1 agonists improved hyperlocomotion compared to control (N=13 studies, k=41 experiments, SMD=1.01, 95%CI: 0.74, 1.27), but seemed less efficacious compared to dopamine D2 receptor antagonists (N=4, k=7, SMD=-0.62, 95%CI: -1.32, 0.08). Limited human and animal data indicated that TAAR1 agonists may regulate presynaptic dopaminergic signalling. Conclusions TAAR1 agonists may be less efficacious than dopamine D2 receptor antagonists already licensed for schizophrenia. The results are preliminary due to the limited number of drugs examined, lack of longer-term data, publication bias, and assay sensitivity concerns in trials associated with large placebo response. Considering their unique mechanism of action, relatively benign side-effect profile and ongoing drug development, further research is warranted. Registration PROSPERO-ID:CRD42023451628.
osl-dynamics, a toolbox for modeling fast dynamic brain activity
Neural activity contains rich spatiotemporal structure that corresponds to cognition. This includes oscillatory bursting and dynamic activity that span across networks of brain regions, all of which can occur on timescales of tens of milliseconds. While these processes can be accessed through brain recordings and imaging, modeling them presents methodological challenges due to their fast and transient nature. Furthermore, the exact timing and duration of interesting cognitive events are often a priori unknown. Here, we present the OHBA Software Library Dynamics Toolbox (osl-dynamics), a Python-based package that can identify and describe recurrent dynamics in functional neuroimaging data on timescales as fast as tens of milliseconds. At its core are machine learning generative models that are able to adapt to the data and learn the timing, as well as the spatial and spectral characteristics, of brain activity with few assumptions. osl-dynamics incorporates state-of-the-art approaches that can be, and have been, used to elucidate brain dynamics in a wide range of data types, including magneto/electroencephalography, functional magnetic resonance imaging, invasive local field potential recordings, and electrocorticography. It also provides novel summary measures of brain dynamics that can be used to inform our understanding of cognition, behavior, and disease. We hope osl-dynamics will further our understanding of brain function, through its ability to enhance the modeling of fast dynamic processes.
The GLM-spectrum: A multilevel framework for spectrum analysis with covariate and confound modelling
Abstract The frequency spectrum is a central method for representing the dynamics within electrophysiological data. Some widely used spectrum estimators make use of averaging across time segments to reduce noise in the final spectrum. The core of this approach has not changed substantially since the 1960s, though many advances in the field of regression modelling and statistics have been made during this time. Here, we propose a new approach, the General Linear Model (GLM) Spectrum, which reframes time averaged spectral estimation as multiple regression. This brings several benefits, including the ability to do confound modelling, hierarchical modelling, and significance testing via non-parametric statistics. We apply the approach to a dataset of EEG recordings of participants who alternate between eyes-open and eyes-closed resting state. The GLM-Spectrum can model both conditions, quantify their differences, and perform denoising through confound regression in a single step. This application is scaled up from a single channel to a whole head recording and, finally, applied to quantify age differences across a large group-level dataset. We show that the GLM-Spectrum lends itself to rigorous modelling of within- and between-subject contrasts as well as their interactions, and that the use of model-projected spectra provides an intuitive visualisation. The GLM-Spectrum is a flexible framework for robust multilevel analysis of power spectra, with adaptive covariate and confound modelling.
Post-stroke upper limb recovery is correlated with dynamic resting-state network connectivity.
Motor recovery is still limited for people with stroke especially those with greater functional impairments. In order to improve outcome, we need to understand more about the mechanisms underpinning recovery. Task-unbiased, blood flow-independent post-stroke neural activity can be acquired from resting brain electrophysiological recordings and offers substantial promise to investigate physiological mechanisms, but behaviourally relevant features of resting-state sensorimotor network dynamics have not yet been identified. Thirty-seven people with subcortical ischaemic stroke and unilateral hand paresis of any degree were longitudinally evaluated at 3 weeks (early subacute) and 12 weeks (late subacute) after stroke. Resting-state magnetoencephalography and clinical scores of motor function were recorded and compared with matched controls. Magnetoencephalography data were decomposed using a data-driven hidden Markov model into 10 time-varying resting-state networks. People with stroke showed statistically significantly improved Action Research Arm Test and Fugl-Meyer upper extremity scores between 3 weeks and 12 weeks after stroke (both P < 0.001). Hidden Markov model analysis revealed a primarily alpha-band ipsilesional resting-state sensorimotor network which had a significantly increased life-time (the average time elapsed between entering and exiting the network) and fractional occupancy (the occupied percentage among all networks) at 3 weeks after stroke when compared with controls. The life-time of the ipsilesional resting-state sensorimotor network positively correlated with concurrent motor scores in people with stroke who had not fully recovered. Specifically, this relationship was observed only in ipsilesional rather in contralesional sensorimotor network, default mode network or visual network. The ipsilesional sensorimotor network metrics were not significantly different from controls at 12 weeks after stroke. The increased recruitment of alpha-band ipsilesional resting-state sensorimotor network at subacute stroke served as functionally correlated biomarkers exclusively in people with stroke with not fully recovered hand paresis, plausibly reflecting functional motor recovery processes.
Evaluating functional brain organization in individuals and identifying contributions to network overlap
Abstract Individual differences in the spatial organization of resting-state networks have received increased attention in recent years. Measures of individual-specific spatial organization of brain networks and overlapping network organization have been linked to important behavioral and clinical traits and are therefore potential biomarker targets for personalized psychiatry approaches. To better understand individual-specific spatial brain organization, this paper addressed three key goals. First, we determined whether it is possible to reliably estimate weighted (non-binarized) resting-state network maps using data from only a single individual, while also maintaining maximum spatial correspondence across individuals. Second, we determined the degree of spatial overlap between distinct networks, using test-retest and twin data. Third, we systematically tested multiple hypotheses (spatial mixing, temporal switching, and coupling) as candidate explanations for why networks overlap spatially. To estimate weighted network organization, we adopt the Probabilistic Functional Modes (PROFUMO) algorithm, which implements a Bayesian framework with hemodynamic and connectivity priors to supplement optimization for spatial sparsity/independence. Our findings showed that replicable individual-specific estimates of weighted resting-state networks can be derived using high-quality fMRI data within individual subjects. Network organization estimates using only data from each individual subject closely resembled group-informed network estimates (which was not explicitly modeled in our individual-specific analyses), suggesting that cross-subject correspondence was largely maintained. Furthermore, our results confirmed the presence of spatial overlap in network organization, which was replicable across sessions within individuals and in monozygotic twin pairs. Intriguingly, our findings provide evidence that overlap between 2-network pairs is indicative of coupling. These results suggest that regions of network overlap concurrently process information from both contributing networks, potentially pointing to the role of overlapping network organization in the integration of information across multiple brain systems.